Algorithmic decision support for operational and strategic advancement of prehospital care

The Swiss rescue service ensures that life-saving measures can be carried out in good time in an emergency. There are approximately 500,000 rescue operations in Switzerland every year, which corresponds to direct costs of around one billion Swiss francs. However, rescue services and preclinical care in general are currently facing a variety of challenges: health authorities are regulating rescue services and emergency rooms with stricter targets. At the same time, the financial burden is increasing and it is difficult to find the necessary skilled personnel to perform the tasks. 

The research project therefore aims to develop a practical decision support system (DSS) that identifies promising strategies for reducing costs and improving the quality of preclinical healthcare in Switzerland. We achieve this by combining mathematical optimization, system dynamics, and participatory methods to find a sound, sustainable, and feasible strategy for preclinical care. This strategy will be partially implemented during the project period to ensure its feasibility. 
Our work will develop new algorithms for optimizing emergency medical services, while also generating and testing participatory processes and strategies that enable the further development of preclinical care with increasing quality and consistent or decreasing costs. This will result in a cross-cantonal strategy for preclinical care planning that provides a decision-making compass for everyone – from emergency medical services to policymakers.

Current system understanding (access data can be requested from Christoph Strauss): https://miro.com/app/board/uXjVJ5MRSeY=/

Project management: Christoph Strauss